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Home page: About Suffering in the World

 Let us Develop a Science of Suffering

This document proposes to create a systematic discipline, called algoscience, in which verifiable and cumulative knowledge concerning the whole variety of matters specifically related to the phenomenon of suffering is sought in accordance with recognized scientific or academic methods. The algoscientific methodology brings forth a new paradigm that allows the phenomenon of suffering to be considered as a specific, primary, empirical object, and worthy of the most objective and comprehensive treatment possible. The question of
terminology is addressed. Preparatory notes are presented concerning algometry, the quantitative study of suffering. Collection and classification (of facts, ideas, documents) are to be done regarding kinds of suffering, people or animals that suffer, causes of suffering, solutions or strategies for suffering, and other topics. A bibliography starts to be developed. Lastly, an appendix section is included.


Methodology is necessary to algoscience in order to develop formally its conceptual basis and its methods. The word methodology here refers to the rationale and the philosophical assumptions that underlie a particular discipline, and that determine how methods (specific principles, practices, procedures) are deployed and interpreted. There can be no detailed guide on how to create a new discipline, but algoscientists could probably draw many lessons from studies on how modern knowledge is pursued, or on how new fields are being developed (e.g. pain research, scientific study of consciousness, positive psychology, sociology of happiness...). For now, the main ideas that are proposed in algoscience methodology can be summed up as follows.

The future characteristics of algoscience are a matter for people to explore, to invent, and to agree upon. This discipline is originally conceived as a comprehensive body of theoretical and practical knowledge. It appears to be a very large discipline, given its specific object, the phenomenon of suffering, and its field, the set of all things that may concern directly or indirectly that formal object. Every modern science, it should be noted, seems to be exceedingly large, or indefinitely expansible. At this time, embryonic algoscience can be handled by "general algoscientists", but eventually the discipline, like others, will probably have to be divided into a number of specialized parts.

Recognition from the academic community will come to algoscience inasmuch as its "paradigm" helps to produce new theoretical and technical knowledge about suffering and its management. But prior to any demonstrative results, the following considerations may invite confidence in the new paradigm.

  • Algoscience considers the phenomenon of suffering as the "specific object" of a "comprehensive" discipline. For the first time, suffering is dealt with as a whole and intrinsic concern. Until now, this concern has generally been subordinated to other preoccupations in politics, economy, society, religion, morals, philosophy, medicine, psychology, neurology, etc., and advances about suffering have mostly followed from our interest in health, knowledge, love, welfare, security, etc. In algoscience, there is a reversal of perspective: suffering is not only specifically and extensively considered, but it is also the chief concern to which other preoccupations are subordinated. Suffering, in its own specificity, is the matter of algoscience: it is not as such the matter of neuroscience, psychotherapy, social work, or medicine because such disciplines are primarily concerned with aspects of suffering that are specific not to suffering itself, but to neuron and brain, or mind and behavior, or social problems, or health and illness. Hopefully, a general discipline about suffering will allow, in knowledge and action, new progress that other fields cannot make possible.

  • From a scientific point of view, algoscience considers suffering as a conceptually defined phenomenon: events or things in the real world are particular and unique, and it is the role of science to turn them into conceptually defined phenomena or facts that are general and comparable to one another. As a conceptually defined phenomenon, suffering is a kind of abstraction comprising temporal, spatial, subjective or other types of attributes, but devoid of particularities such as a date, a place, a specific individual's presence or any other contingent condition of manifestation. This abstractive process makes scientific knowledge possible, because it makes it "verifiable". It may be reminded that there is no truth in science, but only theories that at all time can be proved or disproved. In the same line of thought, it may be noted that all matters that may concern suffering can be treated in algoscience, but only inasmuch as they are amenable to scientific verification. Religious or philosophical viewpoints on suffering, for example, may be approached from a scientific point of view by algoscience or other sciences, although they belong in their specificity to religion or philosophy.

  • Algoscience considers suffering as an empirical concept, because it is a psychological process that can be observed through the behavior or the functioning of groups, individuals, bodies, brains, neurons… Suffering can be measured and modified, augmented or diminished, started or stopped. Objective correlations can be established, and empirical knowledge can be developed.

  • Algoscience considers suffering with a radical, typically scientific stance of objectivity. It does not value suffering negatively nor positively. Consequently, parts of algoscience that are evaluative (e.g. critical studies of theories), or prescriptive (e.g. developmental studies of antalgic factors), or even factual (e.g. inventorial collections), are scientific only inasmuch as "statements of existence of value" are used rather than "intrinsic value judgments". Criteria must be made explicit, in particular, when suffering is said to be good or bad, useful or useless, acceptable or unacceptable, avoidable or unavoidable, light or severe, etc. Authors of documents in algoscience should mandatorily identify in a formal fashion what, how, and especially "whose" values or interests are taken as parameters in their work. Neutral objectivity in science has often been a heuristic device, and hopefully it will have the same serendipity with suffering. Besides, there is a place for ethics in algoscience. The discipline itself cannot and should not have an ethical position, but students of suffering should have one! In short, algoscience as a discipline has only one purpose: universal knowledge about suffering. By itself, it has no other goal, value, strategy, or program of action.


A new discipline has to develop its own technical vocabulary. In algoscience, the word 'suffering' itself is highly problematic, because its definition remains an elusive matter. For a start, let us simply talk about suffering as the phenomenon of unpleasant feeling. It is proposed to use the ancient Greek word algos, which means suffering, as a convenient root for forming neologisms, alleviating language repetition, and facilitating a new more technical semantics.

The Wikipedia article about suffering has a section about words that are often used ambiguously when dealing with this topic:

The word suffering is sometimes used in the narrow sense of physical pain, but more often it refers to mental or emotional pain, or more often yet to pain in the broad sense, i.e. to any unpleasant feeling, emotion or sensation. The word pain usually refers to physical pain, but it is also a common synonym of suffering. The words pain and suffering are often used both together in different ways. For instance, they may be used as interchangeable synonyms. Or they may be used in 'contradistinction' to one another, as in "pain is inevitable, suffering is optional", or "pain is physical, suffering is mental". Or they may be used to define each other, as in "pain is physical suffering", or "suffering is severe physical or mental pain".

Qualifiers, such as mental, emotional, psychological, and spiritual, are often used for referring to certain types of pain or suffering. In particular, mental pain (or suffering) may be used in relationship with physical pain (or suffering) for distinguishing between two wide categories of pain or suffering. A first caveat concerning such a distinction is that it uses physical pain in a sense that normally includes not only the 'typical sensory experience of physical pain' but also other unpleasant bodily experiences including air hunger, hunger, vestibular suffering, nausea, sleep deprivation, and itching. A second caveat is that the terms physical or mental should not be taken too literally: physical pain or suffering, as a matter of fact, happens through conscious minds and involves emotional aspects, while mental pain or suffering happens through physical brains and, being an emotion, involves important physiological aspects.

The word unpleasantness, which some people use as a synonym of suffering or pain in the broad sense, may refer to the basic affective dimension of pain (its suffering aspect), usually in contrast with the sensory dimension, as for instance in this sentence: “Pain-unpleasantness is often, though not always, closely linked to both the intensity and unique qualities of the painful sensation.” Other current words that have a definition with some similarity to suffering include distress, unhappiness, misery, affliction, woe, ill, discomfort, displeasure, disagreeableness.

A page in preparation concerning the usage and study of terms and expressions used in algoscience can be seen here: Terminology in Algoscience.


Measurement and estimation are of prime importance for most rational activities dealing with suffering, and quantitative studies concerning suffering should be developed as an independent subdiscipline, algometry. See a document in the making, Preparatory Notes for the Measurement of Suffering, which begins as follows:

  • Jeremy Bentham (1748-1832) has prompted much thoughts, in ethical philosophy and in political economy, with his calculus of pleasures and pains. Bentham mentions seven circumstances that affect the value of an actual or potential pleasure or pain: 1- its intensity; 2- its duration; 3- its certainty or uncertainty (how sure are we of its existence?) ; 4- its propinquity (proximity) or remoteness (is it present or more or less future?); 5- its fecundity (how much sensations of the same kind does it necessarily bring about?); 6- its purity (how much sensations of the opposite kind does it necessarily bring about?); 7- its extent (how many people are affected by it?). Modern utilitarians, in their computations, sometimes use hedons and dolors as units for, respectively, pleasures and pains.  
  • The International Society for Panetics has inquired into quantification of matters related to the infliction of suffering (see Quantification Research about Suffering at the ISP). The Society's founder, Ralph Siu, has proposed a unit, the dukkha, for measuring suffering as a product of three factors : intensity, duration and number of persons affected  
  • Pain questionnaires of various kinds (some are quite long) are being developed in medicine for appraising physical pain in patients. The most usual and simple device is the 5 or 10-steps scale, which serves to communicate the intensity degree of a pain. That scale can be numerical, verbal, or visual-analog. Pain may be a purely subjective phenomenon, but its treatment has to be objective; therefore, pain intensity is measured according to "what the patient says", and thus the objective behavioral data collected from what the patient expresses become the basis of an objective pain measurement. Research shows that this method is more reliable than any other for assessing pain in patients. An important book in this area is "Handbook of Pain assessment", by Melzack and Turk. More concerned with suffering as such is the Pictorial Representation of Illness and Self Measure (PRISM), a simple quantitative method of assessing the perceived burden of suffering due to illness.
  • In the field of psychophysiological measurement, various equipments (e.g. stimulus gauges, reflex gauges, nerve impulse recorders, electroencephalograms, computerized tomography scanners, magnetic resonance imaging scanners) are used to probe the measurable organic basis of physical pain or psychological suffering. That field has a long history that should be recapitulated as a part of algometrics. Some important concepts are the dol (a unit of pain), the JND (just noticeable difference), the Weber-Fechner law (the amount of a perception is proportional to the natural logarithm of the stimulus)… Generally, measurable aspects that are most significant to algometry are intensity, acuteness, dullness, aversion, duration, length, frequency, recurrence… It may be noted that as a psychophysiological phenomenon, suffering can be regarded under various aspects relating to neurology, endocrinology, affectivity, cognition, volition… Each aspects may require a special algometric treatment. As to physical pain, several imaging techniques, in addition to lab tests (blood, urine, spinal fluid, biopsy, etc.), are used for investigating and assessing its causes: electroencephalography (EEG), tomography (CAT scan, MRI, etc.), radiography, ultrasonography, thermography, myelography, electromyography, etc. Richard Ryder, on page  64 of his book Painism - A Moral Modernity, mentions the following means for measuring pain in animals (and possibly in infants or other humans with limited communication capabilities): behavior (such as screams, approach or avoidance preferences), autonomic responses (such as heart rate, respiration, galvanic skin response), level of hormones (such as adrenaline, noradrenaline, cortisol), level of pain-associated neurotransmitters, level of endogenous opiates, and with a view to rating their painful experiences for us, Ryder adds that animals can be trained to do something (e.g. pressing a lever) to avoid unpleasant situation or they can be given access to self-medication with analgesics. See also the article Dolorimeter in Wikipedia. On April 11, 2013, the New England Journal of Medicine published an article: An fMRI-Based Neurologic Signature of Physical Pain. See also the AlgiScan (article and video), a device that allows an objective measure of nociception in anesthesia and reanimation. See also Reading Pain in a Human Face: "Can you tell which expressions show real pain and which ones are feigned? A study found that human observers had no better than a 55 percent rate of success, even with training, while a computer was accurate about 85 percent of the time."  
  • In the field of clinical psychology, a number of tests might be used for assessing psychological suffering. The category Clinical psychology tests at Wikipedia includes for instance Beck Hopelessness Scale, Hamilton Rating Scale for Depression, Zung Self-Rating Anxiety Scale, etc. There are also affect measures such as the Positive Affect Negative Affect Schedule (PANAS). In the fields of healthcare and health economics, measures like QALY (quality-adjusted life year) and DALY ( disability-adjusted life year) are used.  
  • Justice, insurance, actuarial science, risk management are fields where suffering may be quantified. In particular, evaluations of suffering are routinely done by the courts for assessing damages. See for instance How do insurance companies and juries assign values to pain and suffering?  
  • Suffering in groups of individuals is sometimes tentatively quantified by using social indicators (e.g. The Human Poverty Index, The Index of Social health), statistics on problems related to suffering (such as illnesses, deaths, crimes, human rights violations...), questions addressed to a sample of a population in a survey poll (like surveys about happiness), indexes made up with various data (e.g. The International Human Suffering Index, The Calvert-Henderson Quality of Life Indicators, Gross national happiness -- Here is a list of other current well-known indices: Social Progress Index, Human Development Index, Millennium Development Goals, Multidimensional Poverty Index, OECD Better Life Index, Bhutan Gross National Happiness, Happy Planet Index), etc. Thus, Gallup Poll, using the Cantril Self-Anchoring Striving Scale, may come to an estimate such as More Than One in 10 "Suffering" Worldwide. The Organisation for Economic Co-operation and Development (OECD) hosts The Global Project on Measuring the Progress of Societies which has a wiki called www.wikiprogress.org on the subject; an entry on Subjective Well-being states, about the methodology of subjective well-being measurement: "The most important proof for the validity and reliability and therefore quality of the methodology is that the answers to subjective questions tend to correlate strongly with other indicators of quality of life (e.g. frequency of smiling, evaluation of a person's satisfaction through family and friends, number of positive emotions). More recent evidence from neuroscience confirm that answers to questions on subjective well-being coincide with measured neurological activities." See also articles in Wikipedia such as Quality-adjusted life year (QALY), Disability-adjusted life year (DALY), Cost-utility analysis (CUA), Microlife, Micromort. Another approach yet is Sentiment analysis which has such application as Software That Knows You're Suffering or the Hedonometer.

(... continued at Preparatory Notes for the Measurement of Suffering...)  


Collecting and classifying are usually among the first activities that are done within a new discipline. It is necessary to collect facts, ideas, documents, and to classify them methodically for convenient retrieval and handling. In algoscience, lists as exhaustive as possible should be set up concerning people or animals who suffer, kinds of suffering, causes of suffering, people and organizations who cause suffering, solutions or strategies relative to suffering, people and organizations who contribute to stop, diminish or prevent excessive suffering, documents having to do with suffering, and many other topics. See a page in preparation: Collecting and Classifying in Algoscience.


It is important in algoscience to develop a bibliographic subspecialty dealing with documents that can be found on paper, or on the Internet, or on other media, and that are relevant to knowledge and action about suffering. See a page in preparation: Bibliography in Study of Suffering.


Last modification: 2022/01/26

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